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A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

Computers in biology and medicine
Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations o...

Novel computer algorithm for cough monitoring based on octonions.

Respiratory physiology & neurobiology
The objective assessment of cough frequency is essential for evaluation of cough and antitussive therapies. Nonetheless, available algorithms for automatic detection of cough sound have limited sensitivity and the analysis of cough sound often requir...
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The role of phase shifts of sensory inputs in walking revealed by means of phase reduction.

Journal of computational neuroscience
Detailed neural network models of animal locomotion are important means to understand the underlying mechanisms that control the coordinated movement of individual limbs. Daun-Gruhn and Tóth, Journal of Computational Neuroscience 31(2), 43-60 (2011) ...

Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks.

Medical image analysis
Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is essential to evaluate the progress of the patient and detect complications. In this context, accurate qu...

A hybrid model based on neural networks for biomedical relation extraction.

Journal of biomedical informatics
Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutiona...

Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

Genome research
Models for predicting phenotypic outcomes from genotypes have important applications to understanding genomic function and improving human health. Here, we develop a machine-learning system to predict cell-type-specific epigenetic and transcriptional...

Radiomics in radiooncology - Challenging the medical physicist.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Noticing the fast growing translation of artificial intelligence (AI) technologies to medical image analysis this paper emphasizes the future role of the medical physicist in this evolving field. Specific challenges are addressed when implem...

Robotic Patterning a Superhydrophobic Surface for Collective Cell Migration Screening.

Tissue engineering. Part C, Methods
Collective cell migration, in which cells migrate as a group, is fundamental in many biological and pathological processes. There is increasing interest in studying the collective cell migration in high throughput. Cell scratching, insertion blocker,...
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A hidden Markov tree model for testing multiple hypotheses corresponding to Gene Ontology gene sets.

BMC bioinformatics
BACKGROUND: Testing predefined gene categories has become a common practice for scientists analyzing high throughput transcriptome data. A systematic way of testing gene categories leads to testing hundreds of null hypotheses that correspond to nodes...